title: Approximating optimal controls for networks when there are combinations of population-level and targeted measures available: chlamydia infection as a case-study.
abstract: Using a modified one-dimensional model for the spread of an SIS disease on a network, we show that the behaviour of complex network simulations can be replicated with a simpler model. This model is then used to design optimal controls for use on the network, which would otherwise be unfeasible to obtain, resulting in information about how best to combine a population-level random intervention with one that is more targeted. This technique is used to minimise intervention costs over a short time interval with a target prevalence, and also to minimise prevalence with a specified budget. When applied to chlamydia, we find results consistent with previous work; that is maximising targeted control (contact tracing) is important to using resources effectively, while high-intensity bursts of population control (screening) are more effective than maintaining a high level of coverage.
authors.affiliation: Centre for Mathematical Biology, University of Bath, Bath, BA2 7AY, UK, J.P.Clarke@bath.ac.uk.
authors.forename: James
authors.initials: J
authors.lastname: Clarke
authors.forename: K A Jane
authors.initials: KA
authors.lastname: White
authors.forename: Katy
authors.initials: K
authors.lastname: Turner
mesh_terms: D002690:Chlamydia Infections / Q000453:epidemiology / Q000517:prevention & control* / Q000635:transmission; D002692:Chlamydia trachomatis; D019295:Computational Biology; D003198:Computer Simulation; D016358:Contact Tracing / Q000191:economics / Q000706:statistics & numerical data; D003365:Costs and Cost Analysis; D005260:Female; D006801:Humans; D008297:Male; D008403:Mass Screening / Q000191:economics / Q000706:statistics & numerical data; D055641:Mathematical Concepts; D008954:Models, Biological; D016012:Poisson Distribution; D013269:Stochastic Processes